Cartilage-defect assessment by measuring thickness of knee MRI: Data from the osteoarthritis initiative

The 18th IEEE International Symposium on Consumer Electronics (ISCE 2014) ◽

10.1109/isce.2014.6884524 ◽

2014 ◽

Author(s):

Yong-woo Lee ◽

Bui Toan ◽

Chunsoo Ahn ◽

Jitae Shin

Keyword(s):

Cartilage Defect ◽

Defect Assessment ◽

Knee Mri ◽

Osteoarthritis Initiative

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Comparison of BLOKS and WORMS scoring systems part I. Cross sectional comparison of methods to assess cartilage morphology, meniscal damage and bone marrow lesions on knee MRI: data from the osteoarthritis initiative

Osteoarthritis and Cartilage ◽

10.1016/j.joca.2010.08.017 ◽

2010 ◽

Vol 18 (11) ◽

pp. 1393-1401 ◽

Author(s):

J.A. Lynch ◽

F.W. Roemer ◽

M.C. Nevitt ◽

D.T. Felson ◽

J. Niu ◽

...

Keyword(s):

Bone Marrow ◽

Scoring Systems ◽

Comparison Of Methods ◽

Cross Sectional ◽

Bone Marrow Lesions ◽

Knee Mri ◽

Osteoarthritis Initiative ◽

Meniscal Damage

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3DMeT: 3D Medical Image Transformer for Knee Cartilage Defect Assessment

10.1007/978-3-030-87589-3_36 ◽

2021 ◽

pp. 347-355

Author(s):

Sheng Wang ◽

Zixu Zhuang ◽

Kai Xuan ◽

Dahong Qian ◽

Zhong Xue ◽

...

Keyword(s):

Cartilage Defect ◽

Medical Image ◽

Knee Cartilage ◽

Defect Assessment

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Texture analysis of bone marrow in knee MRI for classification of subjects with bone marrow lesion — Data from the Osteoarthritis Initiative

Magnetic Resonance Imaging ◽

10.1016/j.mri.2013.01.014 ◽

2013 ◽

Vol 31 (6) ◽

pp. 930-938 ◽

Author(s):

Tong Kuan Chuah ◽

Eric Van Reeth ◽

Kenneth Sheah ◽

Chueh Loo Poh

Keyword(s):

Bone Marrow ◽

Texture Analysis ◽

Bone Marrow Lesion ◽

Knee Mri ◽

Osteoarthritis Initiative

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Fast and accurate global geodesic registrations using knee MRI from the Osteoarthritis Initiative

2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops ◽

10.1109/cvprw.2012.6239247 ◽

2012 ◽

Author(s):

Claire R Donoghue ◽

Anil Rao ◽

Luis Pizarro ◽

Anthony M J Bull ◽

Daniel Rueckert

Keyword(s):

Knee Mri ◽

Osteoarthritis Initiative

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Are structural abnormalities on knee MRI associated with osteophyte development? Data from the Osteoarthritis Initiative

Osteoarthritis and Cartilage ◽

10.1016/j.joca.2021.06.012 ◽

2021 ◽

Author(s):

B.A.M. Snoeker ◽

Ishijima M ◽

Kumm J ◽

Zhang F ◽

Turkiewicz AT ◽

...

Keyword(s):

Knee Mri ◽

Structural Abnormalities ◽

Development Data ◽

Osteoarthritis Initiative

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Knee Cartilage Defect Assessment using Cartilage Thickness Atlas

Journal of Biomedical Engineering Research ◽

10.9718/jber.2015.36.2.43 ◽

2015 ◽

Vol 36 (2) ◽

pp. 43-47

Author(s):

Yong-Woo Lee ◽

Toan Duc Bui ◽

Chunsoo Ahn ◽

Jitae Shin

Keyword(s):

Cartilage Defect ◽

Cartilage Thickness ◽

Knee Cartilage ◽

Defect Assessment

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Robust Global Registration through Geodesic Paths on an Empirical Manifold with Knee MRI from the Osteoarthritis Initiative (OAI)

Biomedical Image Registration - Lecture Notes in Computer Science ◽

10.1007/978-3-642-31340-0_1 ◽

2012 ◽

pp. 1-10 ◽

Author(s):

Claire R. Donoghue ◽

Anil Rao ◽

Anthony M. J. Bull ◽

Daniel Rueckert

Keyword(s):

Global Registration ◽

Knee Mri ◽

Geodesic Paths ◽

Osteoarthritis Initiative

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Learning-Based Cost Functions for 3-D and 4-D Multi-Surface Multi-Object Segmentation of Knee MRI: Data From the Osteoarthritis Initiative

IEEE Transactions on Medical Imaging ◽

10.1109/tmi.2017.2781541 ◽

2018 ◽

Vol 37 (5) ◽

pp. 1103-1113 ◽

Author(s):

Satyananda Kashyap ◽

Honghai Zhang ◽

Karan Rao ◽

Milan Sonka

Keyword(s):

Object Segmentation ◽

Cost Functions ◽

Knee Mri ◽

Osteoarthritis Initiative

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Deep Learning‐based Segmentation of Knee MRI for Fully Automatic Sub‐Regional Morphological Assessment of Cartilage Tissues: Data from the Osteoarthritis Initiative

Journal of Orthopaedic Research® ◽

10.1002/jor.25150 ◽

2021 ◽

Author(s):

Egor Panfilov ◽

Aleksei Tiulpin ◽

Miika T. Nieminen ◽

Simo Saarakkala ◽

Victor Casula

Keyword(s):

Deep Learning ◽

Knee Mri ◽

Osteoarthritis Initiative ◽

Fully Automatic ◽

Morphological Assessment

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Automated Segmentation of Knee MRI Using Hierarchical Classifiers and Just Enough Interaction Based Learning: Data from Osteoarthritis Initiative

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016 - Lecture Notes in Computer Science ◽

10.1007/978-3-319-46723-8_40 ◽

2016 ◽

pp. 344-351 ◽

Author(s):

Satyananda Kashyap ◽

Ipek Oguz ◽

Honghai Zhang ◽

Milan Sonka

Keyword(s):

Automated Segmentation ◽

Knee Mri ◽

Osteoarthritis Initiative ◽

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